Natural language processing, including computational semantics and knowledge representation, has become an important component of modern user interfaces. However, systems and methods developed for computational semantics and knowledge representation can be difficult and time consuming to build (often by hand), and may be fragile and not scale well to large corpora and web based scaled language processing. A drawback with current natural language processing systems, including symbolic and subsymbolic approaches is that they are generally resource heavy both in processing and memory. Even with modern computing, fast networks and cheap memory, these systems can take hours, or days to train, and the knowledge base and rules (whether in symbolic or subsymbolic form), may be in the order of gigabytes.